Abstract

Twitter became one of the popular social media in cyberspace. Twitter can be used as a means of disseminating information in their status, this is an opportunity for the parties to disseminate information. This study aims to classify the status of which contain information congestion on Twitter. This study focused on the information content congestion tweet on Twitter. Classification algorithm used is Naive Bayes classifier and K Nearest Neighbor classification model that produces information-based decision trees and rules. This research will prove Classification is done with Twitter data method, Naive Bayes classifier and K-Nearest Neighbor to classify tweets containing information on traffic congestion in Bandar Lampung